In speech recognition technology, removal of effects of background noise is a matter of concern that is important in improving the accuracy of utterance recognition. Filtering techniques of the related art (such as a spectral subtraction method and the Wiener filtering) have a measure of success when background noise is relatively small, but fail to achieve desired results over large background noise since targeted speech sinks into the noise.
To this end, attention has been paid in recent years to approaches that use a probability model of clean speech (utterance speech on which no noise whatsoever is superimposed). These model-based noise reduction methods have been reported to show high performance even over loud background noise. With this regard, Japanese Patent Application Publication No. 2008-298844 (Patent Literature 1) discloses a speech recognition system adopting model-based noise reduction.